Logo image
A Framework for Auditing Robot-Inclusivity of Indoor Environments Based on Lighting Condition
Journal article   Peer reviewed

A Framework for Auditing Robot-Inclusivity of Indoor Environments Based on Lighting Condition

Zimou Zeng, Matthew S. K. Yeo, Charan Satya Chandra Sairam Borusu, M. A. Viraj J. Muthugala, Michael Budig, Mohan Rajesh Elara and Yixiao Wang
Buildings (Basel), Vol.14(4), p.1110
01/04/2024

Abstract

Construction & Building Technology Engineering Engineering, Civil Science & Technology Technology
Mobile service robots employ vision systems to discern objects in their workspaces for navigation or object detection. The lighting conditions of the surroundings affect a robot's ability to discern and navigate in its work environment. Robot inclusivity principles can be used to determine the suitability of a site's lighting condition for robot performance. This paper proposes a novel framework for autonomously auditing the Robot Inclusivity Index of indoor environments based on the lighting condition (RII-lux). The framework considers the factors of light intensity and the presence of glare to define the RII-Lux of a particular location in an environment. The auditing framework is implemented on a robot to autonomously generate a heatmap visually representing the variation in RII-Lux of an environment. The applicability of the proposed framework for generating true-to-life RII-Lux heatmaps has been validated through experimental results.
url
https://doi.org/10.3390/buildings14041110View
Published (Version of record) Open

Metrics

1 Record Views

Details

Logo image